Low dose cone beam CT for image guided adaptive radiotherapy

用于图像引导适应性放射治疗的低剂量锥形束 CT

• 批准号: 8444698
• 负责人: Steve Bin Jiang
• 金额: $ 27.34万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8444698
• 关键词: Algorithms; Chest; Childhood; Clinical; Clinical Protocols; Detection; Dose; Excision; Future; Goals; Hour; Image; Lead; Low Dose Radiation; Morphologic artifacts; Noise; Patients; Performance; Play; Process; Radiation therapy; Research; Resolution; Retinal Cone; Role; Scanning; Series; Speed; Structure; System; Techniques; Testing; Time; Treatment outcome; Update; Variant; Work; base; cancer radiation therapy; clinical application; cone-beam computed tomography; digital; image guided radiation therapy; improved; innovation; next generation; public health relevance; reconstruction

DESCRIPTION (provided by applicant): Cone-beam computed tomography (CBCT) has been broadly used in image guided radiation therapy (IGRT) and adaptive radiation therapy (ART), to acquire the updated patient's geometry for precise targeting and treatment adaptation. However, the repeated use of CBCT during a treatment course has raised a serious concern on excessive x-ray imaging doses delivered to patients, which has greatly limited the maximal exploitation of the potential of modern radiotherapy. Especially for pediatric patients, this concern has prohibited the use of IGRT and ART, leading to compromised treatment outcome. Advanced iterative reconstruction algorithms, based on compressed sensing techniques, have demonstrated tremendous power in reconstructing CBCT images from very few and/or noisy projections, resulting in dramatically reduced imaging dose. However, these algorithms are very computationally inefficient and thus cannot be used in most clinical applications. We have recently made a breakthrough in developing an innovative CBCT reconstruction algorithm with a mathematical structure perfect for parallelization on a graphics processing unit (GPU) platform. Our preliminary results have shown that we can improve the efficiency by a factor of 100 over existing iterative algorithms and reduce the imaging dose by factor of 40~100 compared to the current clinical standard. Our goal is to develop this promising algorithm into a clinically functioning CBCT reconstruction system which can produce high quality CBCT images at extremely low radiation dose (<1% of the current dose) and high speed (< 5 seconds), by pursuing the following two specific aims: SA1. We will develop a GPU-based system to reconstruct high quality CBCT images at ultra-low radiation dose and ultra-high speed. SA2. We will evaluate the system through a series of numerical, phantom, and patient studies, demonstrate the gain in imaging dose reduction, and establish clinical protocols under various clinical conditions. Upon the completion of the proposed project, a clinically ready-to-use CBCT reconstruction system with ultra-low dose and ultra-fast performance will have been systematically developed and evaluated. Clinical introduction of such a system will significantly benefit a large number of patients receiving modern radiotherapy. Especially, our work will for the first time make IGRT and ART clinically available for pediatric patients.

描述（由申请人提供）：锥形束计算机断层扫描（CBCT）已广泛用于图像引导放射治疗（IGRT）和自适应放射治疗（ART），以获取更新的患者几何形状以进行精确定位和治疗适应。然而，治疗过程中重复使用 CBCT 引起了对患者 X 射线成像剂量过高的严重担忧，这极大地限制了现代放射治疗潜力的最大发挥。特别是对于儿科患者，这种担忧禁止使用 IGRT 和 ART，导致治疗结果受损。基于压缩传感技术的先进迭代重建算法在从很少和/或有噪声的投影中重建 CBCT 图像方面表现出了巨大的能力，从而显着减少了成像剂量。然而，这些算法的计算效率非常低，因此不能用于大多数临床应用。我们最近在开发创新的 CBCT 重建算法方面取得了突破，该算法具有非常适合在图形处理单元 (GPU) 平台上并行化的数学结构。我们的初步结果表明，与现有的迭代算法相比，我们可以将效率提高100倍，与当前临床标准相比，将成像剂量减少40~100倍。我们的目标是将这种有前途的算法开发成具有临床功能的 CBCT 重建系统，该系统可以通过追求以下两个目标，以极低的辐射剂量（<当前剂量的 1%）和高速（< 5 秒）生成高质量的 CBCT 图像具体目标：SA1。我们将开发一种基于GPU的系统，以超低辐射剂量和超高速重建高质量的CBCT图像。 SA2。我们将通过一系列数值、模型和患者研究来评估该系统，展示成像剂量减少的收益，并在各种临床条件下建立临床方案。该项目完成后，将系统地开发和评估具有超低剂量和超快速性能的临床即用型CBCT重建系统。这种系统的临床引入将使大量接受现代放射治疗的患者受益匪浅。特别是，我们的工作将首次使 IGRT 和 ART 临床适用于儿科患者。